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java.lang.Objectpapaya.Comparison.TTest
public static class Comparison.TTest
Methods related to comparing two populations. Each method returns an array with the first element containing the t-statistic, and the second corresponding to the p-value, or significance, of rejecting the null hypothesis.
Tests can be:
Test statistics are available for all tests. Methods including "Test" in
in their names perform tests, all other methods return t-statistics. Among
the "Test" methods, double-
valued methods return p-values;
boolean-
valued methods perform fixed significance level tests.
Significance levels are always specified as numbers between 0 and 0.5
(e.g. tests at the 95% level use alpha=0.05
).
Note: Inspired by the stats.inference.TTest class available in the Apache Commons math library.
Method Summary | |
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static float[] |
equalVar(float[] data1,
float[] data2)
Returns the t-statistic and p-value for checking whether the means between the two datasets are different under the assumption that both datasets have equal variances. |
static float[] |
paired(float[] before,
float[] after)
Returns the t-statistic and p-value for checking a pair of dependent samples. |
static float[] |
unequalVar(float[] data1,
float[] data2)
Returns the t-statistic and p-value for checking whether the means between the two datasets are different under the assumption that both datasets have unequal variances. |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Method Detail |
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public static float[] equalVar(float[] data1, float[] data2)
public static float[] unequalVar(float[] data1, float[] data2)
public static float[] paired(float[] before, float[] after)
Both datasets have to have equal lengths.
before
- the dataset before treatment/measurement.after
- the dataset after treatment/measurement.
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